Pre-requisites for learning Data Science

If your aim is to be a Data Analyst, Analytics consultant or a Business Intelligence expert, then this pre-requisites list is not for you. You won't be going deeper into those concepts in your work. However if you wish to make a transition into a data science role in future then this list will definitely help get you a head start.

If you wish to be a data scientist, a machine learning engineer or an Artificial Intelligence Expert, then before you start learning concepts like machine learning and deep learning there are a few pre-requisites for you. There is no hard & fast rule that you will have to learn it from this list only. If you have a good understanding of high school level mathematics, especially topics like linear algebra & probability then you may not need to go through all these pre-requisite content we are discussing here. Just check if any of these need a little revision. 

But if you feel you need a little brush up & need to be ready to be able to grasp all ML concepts with ease without bumping into Linear Algebra or Probability terminologies that seem strange, then this list is definitely for you. If you have a shaky foundation on topics discussed below then, once you covered all these, everything we discuss in this site will make a whole lot sense to you.

I have listed different sources explaining the same concepts. Some people find one explanation helpful and some find the other. Hence please check any of these and if you find it difficult to grasp, always come back and check if the alternatives given in "Or" are easier for you to comprehend.

Basic Linear Algebra:

There already are a great number of terrific content available online on linear algebra & hence we won't be attempting to re-invent the wheel. Here are some great resources for you.

Professor Gilbert Strang's playlist on YouTube. Link here.

You only will have to go through lecture 1 to 11, 14, 15, 16, 18, 20, 21, 29, 30 & 31 & that should be enough. Though if you enjoy learning you can always check the whole playlist. 

Or

The same concepts can be found in Part 3 Linear Algebra: Linear Transformation of MathTheBeautiful. Link here.

Only if you have forgotten it all or you have little knowledge on vectors & matrices then Part 1 of Prof Pavel Greenfield's Linear Algebra series will be of help to you. Link here.

Or

Khan Academy has one of the best video series that explains everything precisely & in great detail. So this can be a great place to begin. Link here.

Probability & Statistics:

Khan Academy's series on Probability.

Never Miss !! :

I highly recommend this playlist from Grant Sanderson's channel 3Blue1Brown. This can be of immense help in building intuition. 

Basics of Python Programming:

This can be learned from anywhere. Be it from a course on coursera, edx, udemy, YouTube or anywhere else, whichever suits you. You only need to be familiar with basics of python & that will be enough to get you started on this platform.

We will be updating this list as we come across any other good resource worth sharing. So stay tuned. 

Once you have learned these concepts please head over to our Probability section to begin your journey into Data Science. To learn data science A-Z do check out our exclusive series Data Science Process End to End. It's FREE !!

PS: None of the above recommendations are sponsored. If you find the same concepts elsewhere you can learn these from there as well. Happy Learning. 🤗